松散回潮出口片烟含水率的过程能力分析与评价

为了对具有自相关性的片烟含水率过程能力更准确的计算,对采集的含水率数据分析,综合考核自相关系数、抽样样本量、不连续抽样等对CPK的影响,为片烟出口含水率过程能力有效、准确的计算和考核提供理论依据。结果显示:1含水率数据间存在正相关时,传统方法高估了过程能力指数;2在考虑自相关影响时,时间间隔的选取很重要;3一阶自回归模型下的最小时间间隔能较好的估计整体过程能力。因此,为片烟出口含水率过程能力有效、准确的计算和考核提供理论依据。     

过程能力指数C_p、C_(pk)与过程性能指数P_p、P_(pk)

过程能力指数是一种广泛应用的产品质量评价工具。不同过程能力指数都有合理一面,但也都有不足之处,选用不当会产生误导。文章研究了过程能力指数C p、Cpk与过程性能指数Pp、Ppk的差别及原因,并分别给出其与不合格率的关系和相应的估计和置信区间。     

基于GARCH模型的极值VaR风险的动态区间估计模型

为了更准确地度量在险值的估计精度及弥补现有极值VaR测算模型的不足,文章基于GARCH方法推导了极值VaR的动态置信区间估计模型,论述了风险资产的极值VaR假设检验方法及基于GARCH方法的置信区间求法,最后用中信(中信标普300)指数对中国股市风险情况作了区间估计及显著性检验的实证分析。结果表明提出的方法较参数法置信区间有更好的估计精度,且能较为敏感地捕捉收益的动态性。     

基于PWM方法的CVaR风险动态区间估计模型

本文基于PWM方法推导了CVaR的动态置信区间估计模型,论述了正态分布下风险资产的CVaR假设检验方法及基于PWM方法的置信区间求法,最后用中信(中信标普300)指数对中国股市风险情况作了区间估计及显著性检验的实证分析。结果表明本文提出的方法较参数法置信区间有更好的估计精度,且能较为敏感地捕捉收益的动态性。     

过程性能指数在现场过程能力评价中的应用探讨

我们知道对过程能力的评价．一般的都是根据过程能力指数的高低来评价．过程能力指数高．表明其满足产品质量的能力高．过程能力指数低．其满足产品质量的能力就低。但是这里的过程能力指数的求得．必须是存过程处于稳态条件下取得的．也就是说必须是该过程存稳态条件下计算的过程能力指数．并用其来评价该过程才有效。     

样本数据缺失情形下泊松过程的强度估计和检验

文章讨论了样本数据缺失情形下泊松过程的强度估计和检验问题。用极大似然估计、矩估计法和最小二乘估计法对强度进行估计,分别得出了极大似然估计强度的迭代方法,矩估计值及最小二乘估计值。证明了矩估计值和最小二乘估计值的无偏性和相合性,导出了其统计量的极限分布。最后,对两个Poisson过程的差异进行了假设检验同时给出渐近置信区间。     

财务风险模拟的可行性分析

计算财务风险的传统方法往往是利用统计模型估计出风险的概率分布，本文提出了使用模拟模型的方法来进行财务风险的模拟，并论证了其可行性和优缺点。     

基于定数截尾样本的指数分布的环境因子估计

讨论了定数截尾样本下,指数分布环境因子的极大似然估计和区间估计,为研究估计的精度,运用随机模拟方法,对环境因子的置信区间的精度进行了讨论。     

基于Monte Carlo模拟的无形资产风险投资评价

无形资产风险投资评价是财务管理的难题之一，其关键是合理、准确地估计无形资产产生的现金流量。由于无形资产产生的现金流量往往具有高度的不确定性，通常采用现金流量的期望值替代，但这样会失去许多有用的信息，容易误导投资者。本文采用Montecado模拟不确定环境下的现金流量，该方法对无形资产风险投资评价具有一定的借鉴意义。     

要准确理解过程能力指数的概念和原理

笔者在某轴承公司现场审核，受审核方向我提出一个他们困惑的问题：“为什么抽取的20个样本质量很好而且全部都合格，而计算出的过程能力指数却很低呢？”为此，他们认为采用过程能力指数方法对轴承产品过程能力的监视和测量不适用。对于受审核方的提问，我的回答是：过程能力的分析方法适用于所有制造业，问题的产生是对过程能力指数的含义没有准确理解，导致在应用中出现上述疑问。     

Generalized confidence intervals for process capability indices in the one-way random model

The method of generalized confidence intervals is proposed as an alternative method for constructing confidence intervals for process capability indices under the one-way random model for balanced as well as unbalanced data. The generalized lower confidence limits and the coverage probabilities for three commonly used capability indices were studied via simulation, separately for balanced and unbalanced cases. Simulation results showed that the generalized confidence interval procedure is quite satisfactory both in the balanced and unbalanced cases. Examples are provided to illustrate the results.     

部分线性单指数动态面板模型的惩罚二次推断函数估计

本文将个体效应与模型的线性部分和非线性部分同时进行估计,构建了惩罚二次推断函数估计法,估计了个体内具有自相关结构的随机效应部分线性单指数动态面板模型。该方法的优点是能够克服由个体效应引起的内生性问题,因此无论滞后因变量处于线性部分还是处于非参数部分均可得到一致有效的估计。进一步,本文证明了该估计方法的一致性和渐近正态性,同时还用Monte Carlo模拟实验评估了该估计方法在有限样本下的表现。     

Modified maximum spacings method for generalized extreme value distribution and applications in real data analysis

This paper analyzes weekly closing price data of the S&P 500 stock index and electrical insulation element lifetimes data based on generalized extreme value distribution. A new estimation method, modified maximum spacings (MSP) method, is proposed and obtained by using interior penalty function algorithm. The standard error of the proposed method is calculated through Bootstrap method. The asymptotic properties of the modified MSP estimators are discussed. Some simulations are performed, which show that the proposed method is not only available for the whole shape parameter space, but is also of high efficiency. The benchmark risk index, value at risk (VaR), is evaluated according to the proposed method, and the confidence interval of VaR is also calculated through Bootstrap method. Finally, the results are compared with those derived by empirical calculation and some existing methods.     

Estimating and Testing Process Precision with Presence of Gauge Measurement Errors

Process capability indices have been widely used in the manufacturing industry. Those capability indices, quantifying process potential and performance, are important for any successful quality improvement activities and quality program implementation. Because of the simplicity and easy of understanding, the precision index C_p has gained its popularity for measuring process consistency. However, the quality of data on the process characteristics relies very much on the gauge measurement. Conclusions about capability of the process just only based on the single numerical value of the index are not reliable. In this paper, we not only conduct the performance of the index C_p with gauge measurement errors, but also present adjusted confidence interval bounds and critical values for capability testing purpose of C_p with unavoidable measurement errors. Our research would help practitioners to determine whether the factory processes meet the capability requirement, and make more reliable decisions.     

Time series modeling of histogram-valued data: The daily histogram time series of S&P500 intradaily returns

Histogram time series (HTS) and interval time series (ITS) are examples of symbolic data sets. Though there have been methodological developments in a cross-sectional environment, they have been scarce in a time series setting. Arroyo, González-Rivera, and Maté (2011) analyze various forecasting methods for HTS and ITS, adapting smoothing filters and nonparametric algorithms such as the k-NN. Though these methods are very flexible, they may not be the true underlying data generating process (DGP). We present the first step in the search for a DGP by focusing on the autocorrelation functions (ACFs) of HTS and ITS. We analyze the ACF of the daily histogram of 5-minute intradaily returns to the S&P500 index in 2007 and 2008. There are clusters of high/low activity that generate a strong, positive, and persistent autocorrelation, pointing towards some autoregressive process for HTS. Though smoothing and k-NN may not be the true DGPs, we find that they are very good approximations because they are able to capture almost all of the original autocorrelation. However, there seems to be some structure left in the data that will require new modelling techniques. As a byproduct, we also analyze the [90,100%] quantile interval. By using all of the information contained in the histogram, we find that there are advantages in the estimation and prediction of a specific interval.     

基于MINITAB的质量管理分析

本文应用MINITAB软件对温州某制造公司轴锻件中平衡轴的质量数据进行了质量控制分析,通过对质量数据的正态性检验、控制图绘制以及过程能力指数的计算等方式,判断出生产过程的质量现状,为企业改进产品质量提供了有效参考。     

Generalized least squares inference in panel and multilevel models with serial correlation and fixed effects

In this paper, I consider generalized least squares (GLS) estimation in fixed effects panel and multilevel models with autocorrelation. The presence of fixed effects complicates implementation of GLS as estimating the fixed effects will typically render standard estimators of the covariance parameters necessary for obtaining feasible GLS estimates inconsistent. I focus on the case where the disturbances follow an AR(p) process and offer a simple to implement bias-correction for the AR coefficients. The usefulness of GLS and the derived bias-correction for the parameters of the autoregressive process is illustrated through a simulation study which uses data from the Current Population Survey.     

Interval estimation for the two-parameter exponential distribution under progressive censoring

The interval estimation of the scale parameter and the joint confidence region of the parameters of two-parameter exponential distribution under Type II progressive censoring is proposed. In addition, the simulation study for the performance of all proposed pivotal quantities is done in this paper. The criteria of minimum confidence length and minimum confidence area are used to obtain the optimal estimation. The predictive intervals of the future observation and the future interarrival times based on the Type II progressive censored sample are also provided. One biometrical example is also given to illustrate the proposed methods.     

Interval Estimation for the Two-Parameter Exponential Distribution Based on the Doubly Type II Censored Sample

The interval estimation of the scale parameter and the joint confidence region of the parameters of two-parameter exponential distribution under doubly Type II censoring is proposed. In addition, the simulation study for the performance of our methods is done in this paper. One biometrical example is also given to illustrate the proposed methods.